1 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation
Bohan Li, Xin Jin, Jianan Wang +8
Recent diffusion models have demonstrated remarkable performance in both 3D scene generation and perception tasks. Nevertheless, existing methods typically separate these two proce…
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation
Yunnan Wang, Ziqiang Li, Zequn Zhang +5
There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the…
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
Baao Xie, Qiuyu Chen, Yunnan Wang +3
Disentangled representation learning (DRL) aims to identify and decompose underlying factors behind observations, thus facilitating data perception and generation. However, current…
Closed-Loop Unsupervised Representation Disentanglement with -VAE Distillation and Diffusion Probabilistic Feedback
Xin Jin, Bohan Li, BAAO Xie +5
Representation disentanglement may help AI fundamentally understand the real world and thus benefit both discrimination and generation tasks. It currently has at least three unreso…